Objective:
This study aims to asses the patients' compliance with essential hypertension in respect to antihypertensive
medications, follow-up, dietary pattern and health habits, to identify the associated long-term complications, and
to find out the relationship between patient's compliance, and demographic characteristics such as age, gender,
level of education, and duration of disease.
Methodology:
A descriptive study was carried out in Nasiriyah Teaching Hospital to achieve presented objectives .
Results:
The results of the study revealed that there were a significant association between educational level and total
patient's compliance, a significant association was found between the duration of disease and complications, the
majority (63%) of the sample was non-complaint, most of them was males with low level of education and
(70%) of them had complications. A greater number (21%) suffering from (Cerebrovascular accident).
Recommendation:
The research recommends that establishing well-equipped specialized hypertension clinics, educational program
should be designed, antihypertensive drugs should be supported by government, antihypertensive medications
must be obtained from the out patient clinic to avoid buying them from private pharmacies to maintain patients
compliance, and further study can be conducted in Iraq to determine the impact of non-compliance of patients
with essential hypertension.
In this paper we reported the microfabrication of three-dimensional structures using two-photon polymerization (2PP) in a mixture of MEH-PPV and an acrylic resin. Femtosecond laser operating at 800nm was employed for the two-photon polymerization processes. As a first step in this project we obtained the better composition in order to fabricate microstructers of MEH-PPV in the resin via two-photon polymerzation. Acknowledgement:This research is support by Mazur Group, Harvrad Universirt.
This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.
Spelling correction is considered a challenging task for resource-scarce languages. The Arabic language is one of these resource-scarce languages, which suffers from the absence of a large spelling correction dataset, thus datasets injected with artificial errors are used to overcome this problem. In this paper, we trained the Text-to-Text Transfer Transformer (T5) model using artificial errors to correct Arabic soft spelling mistakes. Our T5 model can correct 97.8% of the artificial errors that were injected into the test set. Additionally, our T5 model achieves a character error rate (CER) of 0.77% on a set that contains real soft spelling mistakes. We achieved these results using a 4-layer T5 model trained with a 90% error inject
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